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76 lines
3.3 KiB
Python
76 lines
3.3 KiB
Python
# Stubs for random
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# Ron Murawski <ron@horizonchess.com>
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# Updated by Jukka Lehtosalo
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# based on https://docs.python.org/2/library/random.html
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# ----- random classes -----
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import _random
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from typing import AbstractSet, Any, Callable, Iterator, List, MutableSequence, Protocol, Sequence, TypeVar, Union, overload
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_T = TypeVar("_T")
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_T_co = TypeVar("_T_co", covariant=True)
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class _Sampleable(Protocol[_T_co]):
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def __iter__(self) -> Iterator[_T_co]: ...
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def __len__(self) -> int: ...
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class Random(_random.Random):
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def __init__(self, x: object = ...) -> None: ...
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def seed(self, x: object = ...) -> None: ...
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def getstate(self) -> _random._State: ...
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def setstate(self, state: _random._State) -> None: ...
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def jumpahead(self, n: int) -> None: ...
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def getrandbits(self, k: int) -> int: ...
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@overload
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def randrange(self, stop: int) -> int: ...
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@overload
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def randrange(self, start: int, stop: int, step: int = ...) -> int: ...
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def randint(self, a: int, b: int) -> int: ...
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def choice(self, seq: Sequence[_T]) -> _T: ...
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def shuffle(self, x: MutableSequence[Any], random: Callable[[], None] = ...) -> None: ...
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def sample(self, population: _Sampleable[_T], k: int) -> List[_T]: ...
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def random(self) -> float: ...
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def uniform(self, a: float, b: float) -> float: ...
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def triangular(self, low: float = ..., high: float = ..., mode: float = ...) -> float: ...
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def betavariate(self, alpha: float, beta: float) -> float: ...
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def expovariate(self, lambd: float) -> float: ...
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def gammavariate(self, alpha: float, beta: float) -> float: ...
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def gauss(self, mu: float, sigma: float) -> float: ...
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def lognormvariate(self, mu: float, sigma: float) -> float: ...
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def normalvariate(self, mu: float, sigma: float) -> float: ...
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def vonmisesvariate(self, mu: float, kappa: float) -> float: ...
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def paretovariate(self, alpha: float) -> float: ...
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def weibullvariate(self, alpha: float, beta: float) -> float: ...
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# SystemRandom is not implemented for all OS's; good on Windows & Linux
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class SystemRandom(Random): ...
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# ----- random function stubs -----
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def seed(x: object = ...) -> None: ...
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def getstate() -> object: ...
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def setstate(state: object) -> None: ...
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def jumpahead(n: int) -> None: ...
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def getrandbits(k: int) -> int: ...
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@overload
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def randrange(stop: int) -> int: ...
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@overload
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def randrange(start: int, stop: int, step: int = ...) -> int: ...
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def randint(a: int, b: int) -> int: ...
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def choice(seq: Sequence[_T]) -> _T: ...
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def shuffle(x: MutableSequence[Any], random: Callable[[], float] = ...) -> None: ...
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def sample(population: _Sampleable[_T], k: int) -> List[_T]: ...
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def random() -> float: ...
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def uniform(a: float, b: float) -> float: ...
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def triangular(low: float = ..., high: float = ..., mode: float = ...) -> float: ...
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def betavariate(alpha: float, beta: float) -> float: ...
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def expovariate(lambd: float) -> float: ...
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def gammavariate(alpha: float, beta: float) -> float: ...
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def gauss(mu: float, sigma: float) -> float: ...
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def lognormvariate(mu: float, sigma: float) -> float: ...
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def normalvariate(mu: float, sigma: float) -> float: ...
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def vonmisesvariate(mu: float, kappa: float) -> float: ...
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def paretovariate(alpha: float) -> float: ...
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def weibullvariate(alpha: float, beta: float) -> float: ...
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